1-2 October 2026

If you have a multivalued treatment or groups that switch in and out of treatment, traditional difference-in-differences (DID) estimators are of little use. The new xtswitchdid command handles both…

5–6 November 2026

Explore Stata in Chinese, Japanese, Korean, Spanish, and Swedish.

In this release, we build on previous Do-file Editor enhancements, with focus on customization. We provide users the possibility of enabling only features useful to them.

Stata at Biopharm Workshop 2026.

1-2 October 2026

With the new -cfregress- and -cfprobit- commands, you can fit control-function linear and probit models, which provide a flexible alternative to traditional instrumental-variables (IV) methods for…

YouTube video by Platypus Economics with Justin Wolfers

Taking a class that uses Stata but not sure where to start? Start here.

5–6 November 2026

Absorb not just one but multiple high-dimensional categorical variables in your linear and fixed-effects linear models with option -absorb()- of commands -areg-, -xtreg-, and -ivregress 2sls-.

17 September 2026 in Milan

1-2 October 2026

Stata's new financial statistics suite of commands provides tools to manage and analyze financial data. The new commands simplify workflows and expand on the data management, statistics, reporting,…

Learn how to interact with Stata 19 using the menu system and dialog boxes, the Command window, and the Do-file Editor. We also show you some valuable, time-saving tips for improving your workflow in…

New to Stata? Ready to analyze your data but not sure where to start? Start here.

3-4 September 2026 in London

We often determine whether a more efficient random effects model can be used instead of a fixed effects model using a Hausman specification test with -hausman-. But this works only for linear…

With the new -finregress- command, you can run financial regressions. The time-series method and the Fama-MacBeth method are supported.

5–6 November 2026

A history of StataNow update announcements.

With -bayesboot- implement Bayesian bootstrap to obtain inferences based on the posterior distribution of observations, obtain the importance weights of each observation, or assign probabilities to…

Stata's mixed command now supports spatial error covariance structures, letting you model correlation between errors as a function of distance computed from coordinate variables.

Absorb multiple high-dimensional categorical variables in your line...